Biology subjects

Calabrese, G. M.

Publications and source records attributed to Calabrese, G. M..

5 recordsLinked to original sources

bioRxiv2024

Cell type-specific network analysis in Diversity Outbred mice identifies genes potentially responsible for human bone mineral density GWAS associations

Genome-wide association studies (GWASs) have identified many sources of genetic variation associated with bone mineral density (BMD), a clinical predictor of fracture risk and osteoporosis. Aside from the identification of causal genes, other difficult challenges to informing GWAS include characterizing the roles of predicted causal genes in disease and providing additional functional context, such as the cell type predictions or biological pathways in which causal genes operate. Leveraging single-cell transcriptomics (scRNA-seq) can assist in informing BMD GWAS by linking disease-associated variants to genes and providing a cell type context for which these causal genes drive disease. Here, we use large-scale scRNA-seq data from bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) from Diversity Outbred (DO) mice to generate cell type-specific networks and contextualize BMD GWAS-implicated genes. Using trajectories inferred from the scRNA-seq data that map cell state transitions, we identify networks enriched with genes that exhibit the most dynamic changes in expression across trajectories. We discover 21 network driver genes, which are likely to be causal for human BMD GWAS associations that colocalize with expression/splicing quantitative trait loci (eQTL/sQTL). These driver genes, including Fgfrl1 and Tpx2, along with their associated networks, are predicted to be novel regulators of BMD via their roles in the differentiation of mesenchymal lineage cells. In this work, we showcase the use of single-cell transcriptomics from mouse bone-relevant cells to inform human BMD GWAS and prioritize genetic targets with potential causal roles in the development of osteoporosis.

systems biology↗

bioRxiv2022

Evaluation of a scalable approach to generate cell-type specific transcriptomic profiles of mesenchymal lineage cells

Genome-wide association studies (GWASs) have revolutionized our understanding of the genetics of complex diseases, such as osteoporosis; however, the challenge has been converting associations to causal genes. Studies have demonstrated the utility of transcriptomics data in linking disease-associated variants to genes; though for osteoporosis, few population transcriptomics datasets have been generated on bone or bone cells, and an even smaller number have profiled individual cell-types. To begin to evaluate approaches to address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions, a popular model of osteoblast differentiation and activity, from five Diversity Outbred (DO) mice using single-cell RNA-seq (scRNA-seq). The goal of the study was to determine if BMSCs could serve as a model for the generation of cell-type specific transcriptomic profiles of mesenchymal lineage cells derived from large populations of mice to inform genetic studies. We demonstrate that dissociation of BMSCs from a heavily mineralized matrix had little effect on viability or their transcriptomic signatures. Furthermore, we show that BMSCs cultured under osteogenic conditions are diverse and consist of cells with characteristics of mesenchymal progenitors, marrow adipogenic lineage precursors (MALPs), osteoblasts, osteocyte-like cells, and immune cells. Importantly, all cells were nearly identical from a transcriptomic perspective to cells isolated directly from bone. We also demonstrated the ability to multiplex single cells and subsequently assign cells to their "mouse-of-origin" using demultiplexing approaches based on genotypes inferred from coding SNPs. We employed scRNA-seq analytical tools to confirm the biological identity of profiled cell-types. SCENIC was used to reconstruct gene regulatory networks (GRNs) and we showed that identified cell-types show GRNs expected of osteogenic and pre-adipogenic lineage cells. Further, CELLECT analysis showed that osteoblasts, osteocyte-like cells, and MALPs captured a significant component of BMD heritability. Together, these data suggest that BMSCs cultured under osteogenic conditions coupled with scRNA-seq can be used as a scalable and biologically informative model to generate cell-type specific transcriptomic profiles of mesenchymal lineage cells in large mouse, and potentially human, populations.

bioinformatics↗

bioRxiv2020

Systems genetics analyses in Diversity Outbred mice inform human bone mineral density GWAS and identify Qsox1 as a novel determinant of bone strength

Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we used Diversity Outbred (DO) mice to directly address these limitations by performing the first systems genetics analysis of 55 complex skeletal phenotypes. We applied a network approach to cortical bone RNA-seq data to discover 72 genes likely to be causal for human BMD GWAS associations, including the novel genes SERTAD4 and GLT8D2. We also performed GWAS in the DO for a wide-range of bone traits and identified Qsox1 as a novel gene influencing cortical bone accrual and bone strength. Our results provide a new perspective on the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.

genetics↗

bioRxiv2019

Identification of a core module for bone mineral density through the integration of a co-expression network and GWAS data

Recently, the \"omnigenic\" model of the genetic architecture of complex traits proposed two general categories of causal genes, core and peripheral. Core genes are hypothesized to play a direct role in regulating disease; thus, their identification has the potential to reveal critical regulators and novel therapeutic targets. Here, we sought to identify genes with \"core-like\" characteristics for bone mineral density (BMD), one of the most significant predictors of osteoporotic fracture. This was accomplished by analyzing genome-wide association study (GWAS) data through the lens of a cell-type and timepoint-specific gene co-expression network for mineralizing osteoblasts. We identified a single co-expression network module that was enriched for genes implicated by GWAS and partitioned BMD heritability, correlated with in vitro osteoblast mineralization, and enriched for genes, which when mutated in humans or mice, led to a skeletal phenotype. Further characterization of this module identified four novel genes (B4GALNT3, CADM1, DOCK9, and GPR133) located within BMD GWAS loci with colocalizing expression quantitative trait loci (eQTL) and altered BMD in mouse knockouts, suggesting they are causal genetic drivers of BMD in humans. Our network-based approach identified a \"core\" module for BMD and provides a resource for expanding our understanding of the genetics of bone mass.

genetics↗

bioRxiv2018

Mouse Genome-Wide Association and Systems Genetics Identifies Lhfp as a Regulator of Bone Mass

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P=3.1 x 10-12) BMD locus on Chromosome 3@52.5 Mbp that replicated in two seperate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts and its expression was regulated by local expression QTL (eQTL) in multiple tissues. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp-/- displayed increased osteogenic differentiation. Lfhp-/- mice also had elevated BMD due to increased cortical bone mass. In conclusion, we used GWAS and systems genetics in mice to identify Lhfp as a regulator of osteoblast activity and bone mass.

genetics↗